from sklearn_benchmarks.reporting.hp_match import HpMatchReporting
reporting = HpMatchReporting(other_library="onnx", config="config.yml", log_scale=True)
reporting.make_report()
We assume here there is a perfect match between the hyperparameters of both librairies. For a given set of parameters and a given dataset, we compute the speedup
time scikit-learn / time onnx. For instance, a speedup of 2 means that onnx is twice as fast as scikit-learn for a given set of parameters and a given dataset.
KNeighborsClassifier_brute_force¶onnx (1.10.1) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
| estimator | function | n_samples_train | n_samples | n_features | parameters_digest | dataset_digest | mean_duration_sklearn | std_duration_sklearn | n_iter | ... | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | diff_accuracy_scores | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | e70d8e7886766d41f30889506baa1e67 | 2cf49829391aa7891e877f2ed070adf0 | 1.863516 | 0.117614 | NaN | ... | brute | -1 | 1 | 0.663 | 0.332630 | 0.020317 | 1.000 | 5.602372 | 5.612813 | 0.337 |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | e70d8e7886766d41f30889506baa1e67 | 2cf49829391aa7891e877f2ed070adf0 | 0.022580 | 0.001318 | NaN | ... | brute | -1 | 1 | 1.000 | 17.518909 | 0.020043 | 0.757 | 0.001289 | 0.001289 | 0.243 |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 22d5eac4a4146149b35eae6914921514 | 2cf49829391aa7891e877f2ed070adf0 | 2.727397 | 0.029766 | NaN | ... | brute | -1 | 5 | 0.757 | 17.665339 | 0.219245 | 0.882 | 0.154393 | 0.154404 | 0.125 |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 16f94fc93942ff7ece860c9b0f64645f | 2cf49829391aa7891e877f2ed070adf0 | 2.036001 | 0.034826 | NaN | ... | brute | 1 | 100 | 0.882 | 0.302218 | 0.010304 | 1.000 | 6.736870 | 6.740785 | 0.118 |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 16f94fc93942ff7ece860c9b0f64645f | 2cf49829391aa7891e877f2ed070adf0 | 0.019218 | 0.000417 | NaN | ... | brute | 1 | 100 | 1.000 | 17.958458 | 0.024560 | 0.757 | 0.001070 | 0.001070 | 0.243 |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2d5f2b2c02d77766434d9e5033b4a76c | 2cf49829391aa7891e877f2ed070adf0 | 2.735226 | 0.044376 | NaN | ... | brute | -1 | 100 | 0.882 | 17.927651 | 0.072061 | 0.663 | 0.152570 | 0.152571 | 0.219 |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | efac583623711d395ddae7a1e881ff68 | 2cf49829391aa7891e877f2ed070adf0 | 2.058051 | 0.054348 | NaN | ... | brute | 1 | 5 | 0.757 | 0.254465 | 0.014530 | 1.000 | 8.087749 | 8.100923 | 0.243 |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | efac583623711d395ddae7a1e881ff68 | 2cf49829391aa7891e877f2ed070adf0 | 0.019395 | 0.000586 | NaN | ... | brute | 1 | 5 | 1.000 | 3.730376 | 0.082546 | 0.922 | 0.005199 | 0.005201 | 0.078 |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | b79d63bb7670c492de5c3befac58fe29 | 2cf49829391aa7891e877f2ed070adf0 | 1.134952 | 0.023934 | NaN | ... | brute | 1 | 1 | 0.663 | 3.733879 | 0.059970 | 0.929 | 0.303961 | 0.304000 | 0.266 |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | e70d8e7886766d41f30889506baa1e67 | 88843f54689e3271092f70126e1de585 | 1.678147 | 0.028749 | NaN | ... | brute | -1 | 1 | 0.896 | 0.279361 | 0.007953 | 1.000 | 6.007099 | 6.009533 | 0.104 |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | e70d8e7886766d41f30889506baa1e67 | 88843f54689e3271092f70126e1de585 | 0.004615 | 0.001554 | NaN | ... | brute | -1 | 1 | 1.000 | 4.157028 | 0.032592 | 0.922 | 0.001110 | 0.001110 | 0.078 |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 22d5eac4a4146149b35eae6914921514 | 88843f54689e3271092f70126e1de585 | 2.584159 | 0.029533 | NaN | ... | brute | -1 | 5 | 0.922 | 4.166782 | 0.051759 | 0.896 | 0.620181 | 0.620229 | 0.026 |
12 rows × 22 columns
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.000 | 7.295 | 0.0 | -1 | 1 | 17.823 | 0.537 | 0.663 | 0.001 | 0.001 | See | See |
| 3 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.000 | 7.101 | 0.0 | -1 | 5 | 0.325 | 0.014 | 1.000 | 0.035 | 0.035 | See | See |
| 6 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.000 | 7.214 | 0.0 | 1 | 100 | 17.350 | 0.290 | 0.882 | 0.001 | 0.001 | See | See |
| 9 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.000 | 7.269 | 0.0 | -1 | 100 | 0.330 | 0.013 | 1.000 | 0.033 | 0.033 | See | See |
| 12 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.001 | 7.325 | 0.0 | 1 | 5 | 3.780 | 0.086 | 0.896 | 0.003 | 0.003 | See | See |
| 15 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.000 | 7.236 | 0.0 | 1 | 1 | 0.237 | 0.008 | 1.000 | 0.047 | 0.047 | See | See |
| 18 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | 0.346 | 0.0 | -1 | 1 | 4.042 | 0.161 | 0.929 | 0.001 | 0.001 | See | See |
| 21 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | 0.332 | 0.0 | -1 | 5 | 0.281 | 0.006 | 1.000 | 0.017 | 0.017 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.864 | 0.118 | 0.000 | 0.002 | -1 | 1 | 0.333 | 0.020 | 1.000 | 5.602 | 5.613 | See | See |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.001 | 0.000 | 0.023 | -1 | 1 | 17.519 | 0.020 | 0.757 | 0.001 | 0.001 | See | See |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.727 | 0.030 | 0.000 | 0.003 | -1 | 5 | 17.665 | 0.219 | 0.882 | 0.154 | 0.154 | See | See |
| 5 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.022 | 0.002 | 0.000 | 0.022 | -1 | 5 | 0.319 | 0.012 | 1.000 | 0.070 | 0.070 | See | See |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.036 | 0.035 | 0.000 | 0.002 | 1 | 100 | 0.302 | 0.010 | 1.000 | 6.737 | 6.741 | See | See |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.019 | 0.000 | 0.000 | 0.019 | 1 | 100 | 17.958 | 0.025 | 0.757 | 0.001 | 0.001 | See | See |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.735 | 0.044 | 0.000 | 0.003 | -1 | 100 | 17.928 | 0.072 | 0.663 | 0.153 | 0.153 | See | See |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.002 | 0.000 | 0.023 | -1 | 100 | 0.315 | 0.011 | 1.000 | 0.073 | 0.073 | See | See |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.058 | 0.054 | 0.000 | 0.002 | 1 | 5 | 0.254 | 0.015 | 1.000 | 8.088 | 8.101 | See | See |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.019 | 0.001 | 0.000 | 0.019 | 1 | 5 | 3.730 | 0.083 | 0.922 | 0.005 | 0.005 | See | See |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.135 | 0.024 | 0.001 | 0.001 | 1 | 1 | 3.734 | 0.060 | 0.929 | 0.304 | 0.304 | See | See |
| 17 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.019 | 0.001 | 0.000 | 0.019 | 1 | 1 | 0.247 | 0.012 | 1.000 | 0.078 | 0.078 | See | See |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.678 | 0.029 | 0.000 | 0.002 | -1 | 1 | 0.279 | 0.008 | 1.000 | 6.007 | 6.010 | See | See |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.005 | 0.002 | 0.000 | 0.005 | -1 | 1 | 4.157 | 0.033 | 0.922 | 0.001 | 0.001 | See | See |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.584 | 0.030 | 0.000 | 0.003 | -1 | 5 | 4.167 | 0.052 | 0.896 | 0.620 | 0.620 | See | See |
| 23 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.010 | 0.005 | 0.000 | 0.010 | -1 | 5 | 0.275 | 0.005 | 1.000 | 0.038 | 0.038 | See | See |
KNeighborsClassifier_kd_tree¶onnx (1.10.1) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
| estimator | function | n_samples_train | n_samples | n_features | parameters_digest | dataset_digest | mean_duration_sklearn | std_duration_sklearn | n_iter | ... | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | diff_accuracy_scores | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | fe8267e25dadb302ed498e50fabf7ef4 | 1eb6cf1a720a225efb91df0b529b0510 | 0.826547 | 1.011824 | NaN | ... | kd_tree | -1 | 1 | 0.929 | 2.915676 | 0.212761 | 1.000 | 0.283484 | 0.284238 | 0.071 |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | fe8267e25dadb302ed498e50fabf7ef4 | 1eb6cf1a720a225efb91df0b529b0510 | 0.002777 | 0.000633 | NaN | ... | kd_tree | -1 | 1 | 1.000 | 118.027272 | 0.000000 | 0.946 | 0.000024 | 0.000024 | 0.054 |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | dc74b969bf622bc24ba3bc62c980983b | 1eb6cf1a720a225efb91df0b529b0510 | 1.012278 | 0.332108 | NaN | ... | kd_tree | -1 | 5 | 0.946 | 118.385681 | 0.000000 | 0.951 | 0.008551 | 0.008551 | 0.005 |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 41accfcdcd5c50784bedf6164b63de99 | 1eb6cf1a720a225efb91df0b529b0510 | 5.421563 | 0.349170 | NaN | ... | kd_tree | 1 | 100 | 0.951 | 2.968757 | 0.133299 | 1.000 | 1.826206 | 1.828046 | 0.049 |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 41accfcdcd5c50784bedf6164b63de99 | 1eb6cf1a720a225efb91df0b529b0510 | 0.003874 | 0.000806 | NaN | ... | kd_tree | 1 | 100 | 1.000 | 117.224741 | 0.000000 | 0.946 | 0.000033 | 0.000033 | 0.054 |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 022f7445d43bb1dbc24dc3106c03cb93 | 1eb6cf1a720a225efb91df0b529b0510 | 3.141040 | 0.143311 | NaN | ... | kd_tree | -1 | 100 | 0.951 | 116.579537 | 0.000000 | 0.929 | 0.026943 | 0.026943 | 0.022 |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 84622ba45e941db642965553529e1941 | 1eb6cf1a720a225efb91df0b529b0510 | 1.625557 | 0.200726 | NaN | ... | kd_tree | 1 | 5 | 0.946 | 0.005819 | 0.000324 | 1.000 | 279.358887 | 279.792285 | 0.054 |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 84622ba45e941db642965553529e1941 | 1eb6cf1a720a225efb91df0b529b0510 | 0.001688 | 0.000513 | NaN | ... | kd_tree | 1 | 5 | 1.000 | 0.043705 | 0.001130 | 0.911 | 0.038620 | 0.038633 | 0.089 |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | a9455565db1d8e052a783317c99744ff | 1eb6cf1a720a225efb91df0b529b0510 | 0.859269 | 0.173876 | NaN | ... | kd_tree | 1 | 1 | 0.929 | 0.068548 | 0.006555 | 0.894 | 12.535376 | 12.592562 | 0.035 |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | fe8267e25dadb302ed498e50fabf7ef4 | edf7cb014c2c0910e1c3aaaf8ae633f2 | 0.027149 | 0.012476 | NaN | ... | kd_tree | -1 | 1 | 0.891 | 0.005732 | 0.000102 | 1.000 | 4.736063 | 4.736806 | 0.109 |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | fe8267e25dadb302ed498e50fabf7ef4 | edf7cb014c2c0910e1c3aaaf8ae633f2 | 0.002387 | 0.000322 | NaN | ... | kd_tree | -1 | 1 | 1.000 | 0.042454 | 0.001367 | 0.911 | 0.056231 | 0.056260 | 0.089 |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | dc74b969bf622bc24ba3bc62c980983b | edf7cb014c2c0910e1c3aaaf8ae633f2 | 0.024406 | 0.001728 | NaN | ... | kd_tree | -1 | 5 | 0.911 | 0.042142 | 0.000999 | 0.891 | 0.579137 | 0.579299 | 0.020 |
12 rows × 22 columns
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2.986 | 0.098 | 0.027 | 0.0 | -1 | 1 | 119.164 | 0.000 | 0.929 | 0.025 | 0.025 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.624 | 0.073 | 0.022 | 0.0 | -1 | 5 | 2.885 | 0.179 | 1.000 | 1.256 | 1.259 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.715 | 0.080 | 0.022 | 0.0 | 1 | 100 | 118.157 | 0.000 | 0.951 | 0.031 | 0.031 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.796 | 0.114 | 0.021 | 0.0 | -1 | 100 | 2.948 | 0.113 | 1.000 | 1.287 | 1.288 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.780 | 0.060 | 0.021 | 0.0 | 1 | 5 | 0.056 | 0.016 | 0.891 | 67.675 | 70.526 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.727 | 0.104 | 0.021 | 0.0 | 1 | 1 | 0.006 | 0.000 | 1.000 | 671.177 | 671.564 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.001 | 0.021 | 0.0 | -1 | 1 | 0.067 | 0.001 | 0.894 | 0.011 | 0.011 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.027 | 0.0 | -1 | 5 | 0.006 | 0.000 | 1.000 | 0.100 | 0.100 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.827 | 1.012 | 0.000 | 0.001 | -1 | 1 | 2.916 | 0.213 | 1.000 | 0.283 | 0.284 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 1 | 118.027 | 0.000 | 0.946 | 0.000 | 0.000 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.012 | 0.332 | 0.000 | 0.001 | -1 | 5 | 118.386 | 0.000 | 0.951 | 0.009 | 0.009 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 5 | 2.993 | 0.195 | 1.000 | 0.001 | 0.001 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 5.422 | 0.349 | 0.000 | 0.005 | 1 | 100 | 2.969 | 0.133 | 1.000 | 1.826 | 1.828 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.004 | 0.001 | 0.000 | 0.004 | 1 | 100 | 117.225 | 0.000 | 0.946 | 0.000 | 0.000 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 3.141 | 0.143 | 0.000 | 0.003 | -1 | 100 | 116.580 | 0.000 | 0.929 | 0.027 | 0.027 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.005 | 0.001 | 0.000 | 0.005 | -1 | 100 | 2.942 | 0.152 | 1.000 | 0.002 | 0.002 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.626 | 0.201 | 0.000 | 0.002 | 1 | 5 | 0.006 | 0.000 | 1.000 | 279.359 | 279.792 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.002 | 0.001 | 0.000 | 0.002 | 1 | 5 | 0.044 | 0.001 | 0.911 | 0.039 | 0.039 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.859 | 0.174 | 0.000 | 0.001 | 1 | 1 | 0.069 | 0.007 | 0.894 | 12.535 | 12.593 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 0.006 | 0.000 | 1.000 | 0.185 | 0.185 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.027 | 0.012 | 0.001 | 0.000 | -1 | 1 | 0.006 | 0.000 | 1.000 | 4.736 | 4.737 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 1 | 0.042 | 0.001 | 0.911 | 0.056 | 0.056 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.024 | 0.002 | 0.001 | 0.000 | -1 | 5 | 0.042 | 0.001 | 0.891 | 0.579 | 0.579 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 5 | 0.005 | 0.000 | 1.000 | 0.389 | 0.389 | See | See |
HistGradientBoostingClassifier_best¶onnx (1.10.1) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: learning_rate=0.01, n_iter_no_change=10.0, max_leaf_nodes=100.0, max_bins=255.0, min_samples_leaf=100.0, max_iter=300.0.
| estimator | function | n_samples_train | n_samples | n_features | parameters_digest | dataset_digest | mean_duration_sklearn | std_duration_sklearn | n_iter | ... | max_leaf_nodes | min_samples_leaf | n_iter_no_change | accuracy_score_sklearn | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | diff_accuracy_scores | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | HistGradientBoostingClassifier_best | predict | 100000 | 1000 | 100 | 25b9f14bed7dd5d830c6ccd4dfebbf0c | 8c8fffa8ec4b2d8de833421f9e32beab | 0.120581 | 0.002811 | 300 | ... | 100 | 100 | 10 | 0.824 | 0.430468 | 0.009203 | 1.0 | 0.280115 | 0.280179 | 0.176 |
1 rows × 25 columns
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | HistGradientBoostingClassifier_best | fit | 100000 | 100000 | 100 | 100.029 | 0.0 | 300 | 0.001 | 0.001 | 0.539 | 0.027 | 0.824 | 185.724 | 185.959 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | HistGradientBoostingClassifier_best | predict | 100000 | 1000 | 100 | 0.121 | 0.003 | 300 | 0.007 | 0.0 | 0.43 | 0.009 | 1.0 | 0.28 | 0.28 | See | See |